DBMS > Postgres-XL vs. StarRocks vs. SWC-DB vs. Tkrzw vs. Valentina Server

System Properties Comparison Postgres-XL vs. StarRocks vs. SWC-DB vs. Tkrzw vs. Valentina Server

Editorial information provided by DB-Engines

Name

Description

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

An open source, high-performance columnar analytical database that enables real-time, multi-dimensional, and highly concurrent data analytics

Forked from Apache Doris

A high performance, scalable Wide Column DBMS

A concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet

Object-relational database and reports server

Primary database model

Secondary database models

Document store
Spatial DBMS

Time Series DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	0.53
Rank	#254	Overall
	#117	Relational DBMS

Score	0.93
Rank	#198	Overall
	#93	Relational DBMS

Score	0.08
Rank	#364	Overall
	#13	Wide column stores

Score	0.07
Rank	#372	Overall
	#57	Key-value stores

Score	0.21
Rank	#325	Overall
	#144	Relational DBMS

Website

www.postgres-xl.org

www.starrocks.io

github.com/kashirin-alex/swc-db
www.swcdb.org

dbmx.net/tkrzw

www.valentina-db.net

Technical documentation

www.postgres-xl.org/documentation

docs.starrocks.io/en-us/latest/introduction/StarRocks_intro

valentina-db.com/docs/dokuwiki/v5/doku.php

Developer

The Linux Foundation

since Feb 2023

Alex Kashirin

Mikio Hirabayashi

Paradigma Software

Initial release

2014

since 2012, originally named StormDB

2020

1999

Current release

10 R1, October 2018

2.5.3, March 2023

0.5, April 2021

0.9.3, August 2020

5.7.5

License

Commercial or Open Source

Open Source

Mozilla public license

Open Source

Apache Version 2.0

Open Source

GPL V3

Open Source

Apache Version 2.0

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++, Java

C++

Server operating systems

Linux
macOS

Linux

Linux
macOS

Linux
OS X
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

yes

XML type, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

yes

distributed, parallel query execution

yes

SQL-like query language

yes

APIs and other access methods

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

JDBC
MySQL protocol

Proprietary protocol
Thrift

ODBC

Supported programming languages

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Java

C++

C++
Java
Python
Ruby

.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET

Server-side scripts

Stored procedures

user defined functions

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

horizontal partitioning (by range and hash)

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

MVCC

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

using specific database classes

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Role based access control and fine grained access rights

fine grained access rights according to SQL-standard

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